SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

Showing 20412050 of 10817 papers

TitleStatusHype
TVLT: Textless Vision-Language TransformerCode1
TWEAC: Transformer with Extendable QA Agent ClassifiersCode1
Dense Hierarchical Retrieval for Open-Domain Question AnsweringCode1
UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language ModelsCode1
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-world Document AnalysisCode1
CodeQA: A Question Answering Dataset for Source Code ComprehensionCode1
Designing a Minimal Retrieve-and-Read System for Open-Domain Question AnsweringCode1
Dialog Inpainting: Turning Documents into DialogsCode1
DegreEmbed: incorporating entity embedding into logic rule learning for knowledge graph reasoningCode1
DeFormer: Decomposing Pre-trained Transformers for Faster Question AnsweringCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94Unverified
2FPNet (ensemble)EM90.87Unverified
3IE-NetV2 (ensemble)EM90.86Unverified
4SA-Net on Albert (ensemble)EM90.72Unverified
5SA-Net-V2 (ensemble)EM90.68Unverified
6FPNet (ensemble)EM90.6Unverified
7Retro-Reader (ensemble)EM90.58Unverified
8EntitySpanFocusV2 (ensemble)EM90.52Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49Unverified
10EntitySpanFocus+AT (ensemble)EM90.45Unverified